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Original Research |

IMPROVING PATIENT CARE

Outpatient Electronic Health Records and the Clinical Care and Outcomes of Patients With Diabetes Mellitus

Mary Reed, DrPH; Jie Huang, PhD; Ilana Graetz, BA; Richard Brand, PhD; John Hsu, MD, MBA, MSCE; Bruce Fireman, MA; and Marc Jaffe, MD
[+] Article and Author Information

From Kaiser Permanente Northern California, Oakland, California; University of California, San Francisco, San Francisco, California; Massachusetts General Hospital, Boston, Massachusetts; and Permanente Medical Group, South San Francisco, California.

Disclaimer: Dr. Reed had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Grant Support: By the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK R01DK085070).

Potential Conflicts of Interest: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M11-2670.

Reproducible Research Statement: Study protocol and statistical code: Available from Dr. Reed (e-mail, mary.e.reed@kp.org). Data set: Not available.

Requests for Single Reprints: Mary Reed, DrPH, Division of Research, Kaiser Permanente, 2000 Broadway, Oakland, CA 94612; e-mail, mary.e.reed@kp.org.

Current Author Addresses: Drs. Reed and Huang and Ms. Graetz: Division of Research, Kaiser Permanente, 2000 Broadway, 3rd Floor, Oakland, CA 94612.

Dr. Brand: University of California, San Francisco, Department of Epidemiology & Biostatistics, 185 Berry Street, Suite 5700, San Francisco, CA 94107.

Dr. Hsu: Mongan Institute for Health Policy, Massachusetts General Hospital, Department of Health Care Policy, Harvard Medical School, 50 Staniford Street, 9th Floor, Boston, MA 02114.

Mr. Fireman: Division of Research, Kaiser Permanente, 2000 Broadway, 2nd Floor, Oakland, CA 94612.

Dr. Jaffe: Endocrinology and Internal Medicine, Kaiser South San Francisco Medical Center, 1200 El Camino Real, South San Francisco, CA 94080.

Author Contributions: Conception and design: M. Reed, J. Huang, R. Brand, J. Hsu, B. Fireman, M. Jaffe.

Analysis and interpretation of the data: M. Reed, J. Huang, I. Graetz, R. Brand, J. Hsu, B. Fireman, M. Jaffe.

Drafting of the article: M. Reed, R. Brand, J. Hsu, M. Jaffe.

Critical revision of the article for important intellectual content: M. Reed, J. Huang, I. Graetz, R. Brand, J. Hsu, B. Fireman, M. Jaffe.

Final approval of the article: M. Reed, J. Huang, I. Graetz, R. Brand, J. Hsu, B. Fireman, M. Jaffe.

Statistical expertise: M. Reed, J. Huang, R. Brand, B. Fireman.

Obtaining of funding: M. Reed, R. Brand, J. Hsu.

Administrative, technical, or logistic support: I. Graetz, R. Brand.

Collection and assembly of data: M. Reed, J. Huang.


Ann Intern Med. 2012;157(7):482-489. doi:10.7326/0003-4819-157-7-201210020-00004
Text Size: A A A

Background: Physicians can receive federal payments for meaningful use of complete certified electronic health records (EHRs). Evidence is limited on how EHR use affects clinical care and outcomes.

Objective: To examine the association between use of a commercially available certified EHR and clinical care processes and disease control in patients with diabetes.

Design: Quasi-experimental design with outpatient EHR implementation sequentially across 17 medical centers. Multivariate analyses adjusted for patient characteristics, medical center, time trends, and facility-level clustering.

Setting: Kaiser Permanente Northern California, an integrated delivery system.

Patients: 169 711 patients with diabetes mellitus.

Intervention: Use of a commercially available certified EHR.

Measurements: Drug treatment intensification and hemoglobin A1c (HbA1c) and low-density lipoprotein cholesterol (LDL-C) testing and values.

Results: Use of an EHR was associated with statistically significant improvements in treatment intensification after HbA1c values of 9% or greater (odds ratio, 1.10 [95% CI, 1.05 to 1.15]) or LDL-C values of 2.6 to 3.3 mmol/L (100 to 129 mg/dL) (odds ratio, 1.06 [CI, 1.00 to 1.12]); increases in 1-year retesting for HbA1c and LDL-C levels among all patients, with the most dramatic change among patients with the worst disease control (HbA1c levels ≥9% or LDL-C levels ≥3.4 mmol/L [≥130 mg/dL]); and decreased 90-day retesting among patients with HbA1c levels less than 7% or LDL-C levels less than 2.6 mmol/L (<100 mg/dL). The EHR was also associated with statistically significant reductions in HbA1c and LDL-C levels, with the largest reductions among patients with the worst control (0.06-mmol/L [2.19-mg/dL] reduction among patients with baseline LDL-C levels ≥3.4 mmol/L [≥130 mg/dL]; P < 0.001).

Limitation: The EHR was implemented in a setting with strong baseline performance on cardiovascular care quality measures.

Conclusion: Use of a commercially available certified EHR was associated with improved drug treatment intensification, monitoring, and physiologic control among patients with diabetes, with greater improvements among patients with worse control and less testing in patients already meeting guideline-recommended glycemic and lipid targets.

Primary Funding Source: National Institute of Diabetes and Digestive and Kidney Diseases.

Figures

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Figure.

Staggered EHR implementation by medical center: quasi-experimental study with concurrent controls.

This figure shows the schedule of staggered outpatient EHR implementation across all study medical centers during the study period (2004–2009; dark shade) and the number of study patients at each medical center. After implementation, the EHR completely replaced the paper medical chart and a limited patchwork of preexisting nonintegrated health information technology tools. Use of those early health information technology tools was limited because paper-based alternatives were still in use. EHR = electronic health record.

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Appendix Figure.

EHR implementation order: relationship between mean HbA1c value in preimplementation period and order of EHR implementation, by medical center.

Mean HbA1c values for the 17 medical centers, ordered by the date of their EHR implementation. A linear regression analysis with the mean HbA1c level among all patients in the diabetes registry in 2004 as the dependent variable and order of EHR implementation as the predictor yields a coefficient of 0.00006371 (P = 0.61), indicating that the order of implementation of EHR was not associated with preimplementation diabetes care quality. EHR = electronic health record; HbA1c = hemoglobin A1c.

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